Python — Tutorials · VLSI Mentor

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36Modules

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Two parts, one dependency chain

Part I is a complete Python education that stands on its own — variables, strings, collections, loops, functions, modules, exceptions, files and object-oriented programming, with no VLSI knowledge assumed. Part II builds on it and never re-teaches it, applying the same language to RTL and verification work.

Regex and testing, in full

A nineteen-chapter regular-expression path that builds every pattern symbol by symbol, and a full module on testing automation — golden log fixtures, negative tests, and breaking the parser on purpose to prove the tests can fail.

Automate → parse → report

From fundamentals on simulation metadata to subprocess EDA-tool automation, parallel regressions, robust log/coverage parsers, and self-contained HTML summaries — the full Python automation loop a verification team owns.

Python Complete Curriculum

Your Learning Roadmap

338 chapters · 36 modules — two parts — Python taught from zero, then the Python a semiconductor engineer needs for simulation, regression, logs, EDA tools and reporting.

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Part I — Python Basics & Fundamentals

Python taught from zero: running your first program, variables, operators, strings, lists, tuples, sets, dictionaries, conditions, loops, functions, comprehensions, modules, exceptions, files and object-oriented programming. No VLSI knowledge required.

Module 1

Introduction to Python

1.1What Python Is, and Where It Runs 1.2Programming vs Scripting 1.3Why Python Is Popular, and Where It Is Used 1.4How Python Executes Your Code 1.5The Interactive Prompt vs a .py File 1.6Checking Python Is There, and Which Version 1.7Writing and Running Your First .py File 1.8print(): Making a Script Say Something 1.9Comments, and What the Computer Ignores 1.10Statements, Lines, and Why Indentation Is Not Decoration 1.11When Python Refuses to Run: Reading the Error

Module 2

Variables and Data Types

2.1Values: The Things a Program Works With 2.2Variables and Names That Explain Themselves 2.3What `=` Really Means 2.4Naming Rules, and Names Worth Reading 2.5Assigning Several Variables at Once 2.6Whole Numbers and Decimals 2.7Complex Numbers 2.8True, False, and Nothing at All 2.9Text: Your First Strings 2.10Checking a Type with type()2.11Converting Between Text and Numbers 2.12Dynamic Typing: Names Do Not Have Types 2.13Mutable and Immutable Values 2.14Constants by Convention

Module 3

Operators and Expressions

3.1Expressions: Code That Produces a Value 3.2Arithmetic: + - * / // % **3.3Assignment Operators: += -= *= and Friends 3.4Comparisons: == != < <= > >=3.5and, or, not 3.6Membership and Identity: in, not in, is 3.7Bitwise Operators: & | ^ ~ << >>3.8Precedence, Parentheses and Saying What You Mean

Module 4

Strings

4.1Working With Strings Before Reaching for Regex 4.2Quotes, Escapes and Multi-Line Text 4.3Joining and Repeating Strings 4.4Indexing: Reaching One Character 4.5Slicing: Taking Part of a String 4.6Length and Membership 4.7Case and Whitespace: upper, lower, strip 4.8split(): Breaking a Line Into Fields 4.9join(): Building One String From Many 4.10Searching: startswith, endswith, find, replace 4.11Strings Do Not Change: Immutability 4.12Building Text With f-Strings 4.13Formatting Numbers for Reports

Module 5

Lists

5.1Lists of Tests, Seeds and Log Lines 5.2Indexing and Slicing a List 5.3Changing a List: append, insert, remove, pop 5.4Going Through a List 5.5Sorting and Ordering Results 5.6Combining and Repeating Lists 5.7Lists Inside Lists 5.8Two Names, One List: Copies and References 5.9Building Lists from Other Values

Module 6

Tuples

6.1Tuples as Fixed Records and Keys 6.2The One-Item Tuple Trap 6.3Reading a Tuple: Indexing and Slicing 6.4Tuples Cannot Be Changed 6.5Unpacking a Tuple Into Names 6.6Tuple Methods and Converting Between Tuple and List 6.7Lists or Tuples: Which to Use

Module 7

Sets

7.1What a Set Is 7.2Checking Membership and Looping Over a Set 7.3Changing a Set: add, update, remove, discard 7.4Set Operations: Difference, Union, Intersection 7.5Subsets, Supersets and Disjoint Sets 7.6Sets or Lists, and Removing Duplicates

Module 8

Dictionaries

8.1Key and Value: The Dictionary Mental Model 8.2Dictionaries: One Result per Test 8.3Safe Lookup: in, .get() and the Missing Key 8.4Adding, Updating and Removing Entries 8.5Looping Over keys, values and items 8.6Copying and Building Dictionaries 8.7Nested Results: Test to Seed to Outcome 8.8Dictionaries or Lists: Which to Use 8.9Choosing a Structure: String, List, Tuple, Dict or Set

Module 9

Conditional Statements

9.1if, elif and else 9.2Indentation Is the Block 9.3Comparison and Logical Conditions 9.4Nested and Compound Conditions 9.5What Counts as True: Truthiness 9.6Conditional Expressions 9.7How an if Actually Runs 9.8match for Dispatching on Tool and Status

Module 10

Loops

10.1What Iteration Means 10.2Looping Over Tests, Seeds and Log Lines 10.3Looping Over Strings, Lists, Tuples, Sets and Dictionaries 10.4Counting With range()10.5while Loops, Polling and Retrying 10.6Choosing Between for and while 10.7Stopping Early: break, continue and the First Failure 10.8The else Clause on a Loop 10.9enumerate() and zip()10.10Counters and Accumulators 10.11Nested Loops: Every Test at Every Seed 10.12Loops That Never End, and Other Classic Mistakes

Module 11

Functions

11.1Why Functions Exist: The Same Code, Three Times 11.2Turning a Repeated Sequence Into a Function 11.3Calling a Function: Names, Parentheses and Arguments 11.4Arguments In, Result Out 11.5Defaults and Keyword Arguments 11.6*args and **kwargs 11.7Passing Lists and Dictionaries to Functions 11.8return Is Not print 11.9Returning More Than One Value 11.10Where Names Live, and Why Globals Bite 11.11Docstrings: Saying What a Function Promises 11.12Type Hints 11.13Recursion 11.14lambda: Small Anonymous Functions 11.15Decomposing a Script Into Reusable, Testable Functions

Module 12

Comprehensions

12.1From a Loop to a List Comprehension 12.2List and Dictionary Comprehensions 12.3Filtering and Transforming a Result List 12.4Conditional Expressions Inside Comprehensions 12.5Set Comprehensions 12.6Nested Comprehensions, and Their Limit 12.7When a Loop Reads Better Than a Comprehension

Module 13

Modules, Packages and Imports

13.1What a Module Is, and Why import Exists 13.2import, from ... import, and Naming What You Borrow 13.3Import Aliases 13.4The Standard Library 13.5Importing Your Own File 13.6if __name__ == "__main__": and Why Scripts Use It 13.7Packages and Laying Out a Small Project

Module 14

Errors and Exception Handling

14.1Syntax Errors vs Runtime Errors 14.2Reading a Traceback From the Bottom Up 14.3The Errors Beginners Actually Hit 14.4Exceptions: What They Are and When to Let Them Escape 14.5Handling Several Different Errors 14.6else and finally: Cleanup That Always Runs 14.7Raising an Error on Purpose 14.8Your Own Error Types for Tool and Parse Failures 14.9Why except: pass Destroys a Regression

Module 15

File Handling

15.1Why Programs Use Files 15.2Opening and Reading a File Safely 15.3Text Mode, Encoding and the Invisible Newline 15.4read, readline, readlines — and Which to Use 15.5with: Why Files Close Themselves 15.6Writing Files: Filelists, Reports and Generated Text 15.7Streaming a Multi-Gigabyte Simulation Log 15.8Asking About a Path: exists, is_file, is_dir 15.9Creating, Renaming and Deleting Files 15.10When the Log Is Missing, Empty or Truncated

Module 16

Object-Oriented Programming

16.1Everything Is an Object: Attributes and Methods 16.2Your First Class: Grouping Data and Behaviour 16.3__init__ and self 16.4Instance and Class Attributes 16.5Instance Methods 16.6Changing an Object's State 16.7Encapsulation and the Underscore Convention 16.8Special Methods and __str__16.9Inheritance 16.10Child Classes and super()16.11Method Overriding 16.12Polymorphism 16.13Composition: Objects Containing Objects 16.14From Loose Variables to One Structured Result 16.15Dataclasses for Results a Whole Flow Passes Around 16.16When a Dictionary Is Enough

Part II — Python for VLSI Engineering

The Python fundamentals from Part I applied to real semiconductor engineering workflows, and never re-teaching them: files and project structures, regular expressions and log parsing, command-line tools, EDA environments and tool control, simulation and regression automation, STA and synthesis reports, coverage, reporting, RTL generation, testing, debugging, and maintainable VLSI automation.

Module 17

Thinking Like a VLSI Automation Engineer